Speeding up Stochastic Dynamic Programming with Zero-Delay Convolution - Dean, Brian (Algorithmic Operations Research)

(untitled) (Preeminent Academic Facets Inc., 2010)
We show how a technique from signal processing known as zero-delay convolution can be used to develop more efficient dynamic programming algorithms for a broad class of stochastic optimization problems. This class includes several variants of discrete stochastic shortest path, scheduling, and knapsack problems, all of which involve making a series of decisions over time that have stochastic consequences in terms of the temporal delay between successive decisions. We also correct a flaw in the original analysis [8] of the zero-delay convolution algorithm.